Integrating Artificial Intelligence (AI) into Precision Medicine (PM) is redefining healthcare, enabling personalized treatments tailored to individual patients based on their genetic code, environment, and lifestyle. AI’s ability analyze vast complex datasets, including genomics medical records, facilitates the identification of hidden patterns correlations, which are critical for developing treatment plans. Unsupervised Learning (UL) particularly valuable in PM as it can unstructured...

Alkaptonuria (AKU) is a rare metabolic disorder characterized by the accumulation of homogentisic acid (HGA), leading to progressive ochronosis and joint degeneration. While much known about HGA’s role in tissue damage, molecular mechanisms underlying acute inflammation AKU remain poorly understood. Serum amyloid A (SAA) proteins are key mediators inflammatory response, yet their potential as biomarkers for has not been explored. This study investigated SAA1.1 allele biomarker severity AKU....

Introduction Accurate prediction of immunogenic proteins is crucial for vaccine development and understanding host-pathogen interactions in bacterial diseases, particularly Salmonella infections which remain a significant global health challenge. Methods We developed SHASI-ML, machine learning-based framework predicting species. The model was trained validated using curated dataset experimentally verified non-immunogenic proteins. Three distinct feature groups were extracted from protein...

Chronic pain affects approximately 30% of the global population, posing a significant public health challenge. Despite their widespread use, traditional pharmacological treatments, such as opioids and NSAIDs, often fail to deliver adequate, long-term relief while exposing patients risks addiction adverse side effects. Given these limitations, medical cannabis has emerged promising therapeutic alternative with both analgesic anti-inflammatory properties. However, its clinical efficacy is...

The pharmaceutical industry faces challenges in developing efficient and cost-effective drug delivery systems. Among various applications, antibody-drug conjugates (ADCs) stand out by combining cytotoxic or bioactive agents with monoclonal antibodies (mAbs) for targeted therapies. However, bioconjugation methods can produce different outcomes, including no bioconjugation, depending on the mAb, amino acid residues, linker-payload (LP) system used. In this work, we developed a machine learning...

Computational methods have transformed target and drug discovery, significantly accelerating the identification of biological targets lead compounds. Despite its limitations, in silico molecular docking represents a foundational tool. Molecular Dynamics (MD) simulations, employing accurate force fields, provide near-realistic insights into compound’s behavior within target. However, MD predictions may be unreliable without precise knowledge binding site. Through we investigated 100...

The growing availability of protein structural data from experimental methods and accurate predictive models provides the opportunity to investigate molecular origins rare diseases (RDs) reviewed in Orpha.net database. In this study, we analyzed topology 5728 missense mutation sites involved Mendelian RDs (MRDs), forming basis our bioinformatics investigation. Each site was characterized by side-chain position within overall 3D structure orientation. Atom depth quantitation, achieved using...

Abstract Background Alkaptonuria (AKU) is an ultra-rare autosomal recessive disease caused by a mutation in the homogentisate 1,2-dioxygenase (HGD) gene. One of main obstacles studying AKU, and other diseases, lack standardized methodology to assess severity or response treatment. Quality Life scores (QoL) are reliable way monitor patients’ clinical condition health status. QoL allow evolution diseases suitability treatments taking into account symptoms, general status care satisfaction....

The enzyme 4-hydroxyphenylpyruvate dioxygenase (4-HPPD) is involved in the catabolism of amino acid tyrosine organisms such as bacteria, plants, and animals. It catalyzes conversion to a homogenisate presence molecular oxygen Fe(II) cofactor. This represents key step biosynthesis important compounds, its activity deficiency leads severe, rare autosomal recessive disorders, like tyrosinemia type III hawkinsinuria, for which no cure currently available. 4-HPPD C-terminal tail plays crucial...

Alkaptonuria (AKU) is a rare autosomal recessive metabolic disorder caused by mutations in the homogentisate 1,2-dioxygenase (HGD) gene, leading to accumulation of homogentisic acid (HGA), causing severe inflammatory conditions. Recently, presence serum amyloid A (SAA) has been reported AKU tissues, classifying as novel secondary amyloidosis; AA amyloidosis characterized extracellular tissue deposition fibrils composed fragments SAA. may complicate several chronic conditions, like rheumatoid...

Conventional therapy options for chronic pain are still insufficient and patients most frequently request alternative medical treatments, such as cannabis. Although clinical evidence supports the use of cannabis pain, very little is known about efficacy, dosage, administration methods, or side effects widely used accessible products. A possible solution could be given by pharmacogenetics, with identification several polymorphic genes that may play a role in pharmacodynamics pharmacokinetics...

ApreciseKUre is a multi-purpose digital platform facilitating data collection, integration and analysis for patients affected by Alkaptonuria (AKU), an ultra-rare autosomal recessive genetic disease. It includes genetic, biochemical, histopathological, clinical, therapeutic resources quality of life scores that can be shared among registered researchers clinicians in order to create Precision Medicine Ecosystem (PME). The combination machine learning application analyse re-interpret...

Abstract Alkaptonuria (AKU) is a progressive systemic inherited metabolic disorder primarily affecting the osteoarticular system, characterized by degeneration of cartilage induced ochronosis, ultimately leading to early osteoarthritis (OA). However, investigating AKU pathology in human chondrocytes, which crucial for understanding disease, encounters challenges due limited availability and donor variability. To overcome this obstacle, an vitro model has been established using homogentisic...

Rare diseases affect a growing number of individuals. One key problem for patients and their caregivers is the difficulty in reaching experts associations competent on particular disease. As consequence, caregivers, often family members patient, learn much about disease from own experience. CaregiverMatcher proof concept providing smart solution to build network linked by matching mechanism based graph neural networks. The experience with rare are described node features. Associations care...

The study of rare diseases is important not only for the individuals affected but also advancement medical knowledge and a deeper understanding human biology genetics. wide repertoire structural information now available from reliable accurate prediction methods provides opportunity to investigate molecular origins most reviewed in Orpha.net database. Thus, it has been possible analyze topology missense mutations found 2,535 proteins involved Mendelian (MRD), which form database our...

The study of rare diseases is important not only for the individuals affected but also advancement medical knowledge and a deeper understanding human biology genetics. wide repertoire structural information now available from reliable accurate prediction methods provides opportunity to investigate molecular origins most reviewed in Orpha.net database. Thus, it has been possible analyze topology pathogenic missense variants found 2515 proteins involved Mendelian (MRDs), which form database...

Transient receptor potential vanilloid 1 (TRPV1) was reported to be a putative target for recovery from chronic pain, producing analgesic effects after its inhibition. A series of drug candidates were previously developed, without the ability ameliorate therapeutic outcome. Starting designed compounds, derived hybridization antagonist SB-705498 and partial agonist MDR-652, we performed virtual screening on pharmacophore model built by exploiting Cryo-EM 3D structure nanomolar in complex with...

The secondary and tertiary structure of a protein has primary role in determining its function. Even though many folding prediction algorithms have been developed the past decades — mainly based on assumption that instructions are encoded within sequence experimental techniques remain most reliable to establish structures. In this paper, we searched for signals related formation [Formula: see text]-helices. We carried out statistical analysis large dataset experimentally characterized...

The transmembrane glycoprotein CD93 has been identified as a potential new target to inhibit tumor angiogenesis. Recently, Multimerin-2 (MMRN2), pan-endothelial extracellular matrix protein, ligand for CD93, but the interaction mechanism between these two proteins is yet be studied. In this article, we aim investigate structural and functional effects of induced mutations on binding domain MMRN2. Starting from experimental data, assessed how specific in C-type lectin-like (CTLD) affect...